AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Interferon lambda-3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our high-tech, dedicated method is applied to construct targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

Q8IZI9

UPID:

IFNL3_HUMAN

Alternative names:

Cytokine Zcyto22; Interleukin-28B; Interleukin-28C

Alternative UPACC:

Q8IZI9; A2BDE1; Q6VN56; Q7Z4J3; Q8IWL6

Background:

Interferon lambda-3, known alternatively as Cytokine Zcyto22, Interleukin-28B, and Interleukin-28C, is a pivotal cytokine with antiviral, antitumour, and immunomodulatory activities. It plays a critical role in the antiviral host defense, especially in epithelial tissues, by acting as a ligand for the IL10RB and IFNLR1 receptor complex. This engagement activates the JAK/STAT signaling pathway, leading to the expression of IFN-stimulated genes (ISG) that mediate the antiviral state.

Therapeutic significance:

Understanding the role of Interferon lambda-3 could open doors to potential therapeutic strategies, particularly in enhancing antiviral and antitumor immunity and modulating immune responses.

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